To avoid certain types of security vulnerabilities, computer-program applications should verify that consumed input is well-formed, without making false assumptions about input consistency. Otherwise, security vulnerabilities such as buffer overruns resulting from malformed input and other types of errors may be fatal to proper functioning and results of the application. To locate any such vulnerabilities, software developers often implement “fuzz testing”, or “fuzzing” prior to releasing software. Fuzzing is a software testing technique that typically provides random data (“fuzz”) as computer-program application data inputs. If the application fails in view of such randomly generated data inputs, for example, by crashing, or by failing built-in code assertions, a software developer generally notes and attempts to address the defects. However, conventional software fuzz testing techniques are typically very time consuming and labor intensive, often requiring iterative manual effort and/or use of inefficient automated techniques. For instance, existing fuzzing techniques generally only locate very specific and simple faults, often with poor code coverage. For example, if input includes a checksum which is not properly updated to match other random changes, only the checksum validation code will be verified. Every fuzzer is generally designed to find a different set of vulnerabilities, or bugs.